A lot of people\u2014myself included\u2014have long been talking about how big data changes everything. But big data\u2019s biggest disruption may be in the high-tech labor market. Forget mobile app developers\u2014a front-page story in the Wall Street Journal over the weekend makes it clear that the most in-demand tech skill is now data science.\nAccording to author Elizabeth Dwoskin, these elusive \u201cunicorns,\u201d with the skills to \u201cextract and interpret the explosion of data from Internet clicks, machines and smartphones,\u201d are being fought over with manic intensity. While some have questioned the reality of the data scientist shortage (see How many data scientists does the world really need?), Dwoskin quotes the head of Booz Allen Hamilton\u2019s data science group claiming that \u201canyone with \u2018data science in his or her job title is going to get \u2018100 recruiter\u2019 emails a day.\u201d Even more striking, that\u2019s only one part of the frantic search to fill up to 36,000 openings at up to 6,000 companies.\nOffering salaries of $200,000 to $300,000 for data scientists with just a couple years of experience, tech recruiters are also going after academics with experience in areas like genome mapping and breast cancer research, dangling the big bucks to get them to help figure out what search terms people use and the impact of tiny changes in online ads.\nSee also: Data scientists: IT's new rock stars\nThe Insight Data Science Fellows Program, in Silicon Valley and New York City, claims to be \u201cyour bridge to a career in data science,\u201d offering an \u201cintensive six-week post-doctoral training fellowship bridging the gap between academia and data science.\u201d The programs\u2019 website claims a 100% placement rate (duh) and notes fellows with doctoral backgrounds in astrophysics, biology, statistics, and so on. Academic budget tightening during the recession has helped fuel the trend as well. And Dwoskin quotes one Yelper who complains that "academia is slow and only a few people see your work."\nThat\u2019s all good if you\u2019re one of the unicorns, or a tech company that can afford to pay big bucks to hire them. But what\u2019s the effect of this trend on the larger world? If the smartest big data analysis is focusing on helping Task Rabbit do more efficient scheduling, what the prognosis for breast cancer research they\u2019re no longer doing?\nLast year, I interviewed IBM\u2019s Grady Booch about the idea that with big data comes big responsibility. Booch was concerned about the misuse of data and its unintended consequences\u2014and said "technology professionals have a responsibility to be cognizant of the possible effects of the data we collect and analyze to raise the awareness of the public and the lawmakers." We didn\u2019t even discuss the possibility that the best and brightest would be drawn away from the most important work to help.\nThe long-term solution to these issues no doubt lies in better automation of data analysis so data scientists aren\u2019t needed for routine analyses. That\u2019s a holy grail for many companies, but no matter how successful that becomes, it\u2019s unlikely to temper the need for highly competent data scientists in the age of big data. The elite data scientists will just find harder and harder problems to work on. And we don\u2019t seem to be running out of those.